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Academic literature on the topic 'Telecom operator's revenue growth strategies'
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Journal articles on the topic "Telecom operator's revenue growth strategies"
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Jafor, A. H. M., MD Sheam Arafat, Mir Abrar Hossain, and Mohammad Majharul Islam. "Survival Strategies for Telecom Operators in the Age of OTT Disruption: A Business Model Analysis of Revenue Diversification and Market Adaptation." American Journal of Management and Economics Innovations 07, no. 05 (2025): 09–32. https://doi.org/10.37547/tajmei/volume07issue05-02.
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The fast growth of Over-the-Top (OTT) services disrupted conventional telecom revenue streams which now demands operators to develop new business approaches. Telecom corporations need essential survival techniques to preserve profitability while operating in an OTT-dominant market structure according to this research. The research utilizes a blended methodology that combines financial data within the industry with case examples and market pattern analyses to study the success of revenue-stream redirection strategies and market transition methods. Telephone and SMS revenue streams diminished continuously because of OTT competition so telecom operators must now focus on subscription packaging, enterprise solutions along with infrastructure revenue streams. Telecom resilience depends on three main factors: affiliations with OTT providers and government rules along with investments to develop new innovations in 5G technology and AI-powered network optimization systems. This paper develops an extensive framework for digital disruption management that helps telecom operators protect their business sustainability through the technological changes. This research connects academic discoveries to industrial field experiences which generates concrete recommendations useful for telecom companies and policy makers and stakeholders involved in digital system operations. The research results demonstrate why telecom entities need to adopt innovative and agile approaches when creating their strategic plans. Future scientific research needs to study how these adaptation techniques affect telecommunication businesses across various markets through extended research periods.
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Ahmed, Awwad. "The impact of over-the-top service providers on the Global Mobile Telecom Industry: A quantified analysis and recommendations for recovery." World Journal of Advanced Research and Reviews 21, no. 1 (2024): 1638–69. https://doi.org/10.5281/zenodo.13337079.
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Telecom industry is significantly evolving all over the globe than ever. Mobile users’ number is increasing remarkably. Telecom operators are investing to get more users connected and to improve user experience, however, they are facing various challenges. Decrease of main revenue streams of voice calls, SMS (Short Message Service) and LDC (Long distance calls) with a significant increase in data traffic. In contrary, with free cost, OTT (Over the top) providers such as WhatsApp and Facebook communication services rendered over networks that built and owned by MNOs. Recently, OTT services gradually substituting the traditional MNOs` services and became ubiquitous with the help of the underlying data services provided by MNOs. The OTTs` services massive penetration into telecom industry is driving the MNOs to reconsider their strategies and revenue sources. <strong>Objective</strong>: The research objective is to critically evaluate the impact of OTT providers on MNOs. With the empirical evidences, the research explores a quantified impact of OTTs on MNOs main revenue streams, and breakdown this impact to highlight effect`s significance. Followed by a statistical trend analysis of global MNOs` revenue over the last decade. Additionally, the research aims to compile, evaluate, and analyze set of former proposed strategies for MNOs to overcome the OTTs` impact. <strong>Methods</strong>: Referring to available open source raw data collected from GSMA and official telecommunications regulatory authorities worldwide, the research develops a statistical model based on regression and extrapolation to analyze the global MNOs` revenue trend. <strong>Findings</strong>: This study reveals a hidden revenue loss for global telecommunications industry represented in all MNOs all over the world. The study corelates the hidden revenue loss to OTTs evolution. The study finds out that SMS is the most impacted traditional service of MNOs and predicted that it will vanish at quarter 4 of 2022. <strong>Recommendations</strong>: MNOs to apply 4 different strategies varying from competing to partnering with OTTs based on the services overlapping level and OTT size. MNOs need to target OPEX and CAPEX reductions and develop their own multi-functional customer-oriented OTT application.
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Zhao, Li, and Hua Ying Shu. "Development Strategies of Data Business for China Telecom Operators in the Background of Mobile Internet." Applied Mechanics and Materials 411-414 (September 2013): 680–83. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.680.
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The thesis firstly analyzes challenges and opportunities of mobile internet: the business model will be subverted; the core business will be alternated and the value of network resource will be lowered. In addition to that, operators can enhance pipeline intelligence and rebuild the correlation of traffic growth and revenue growth. Secondly the thesis gives the advice of enhancing network capabilities and improving the value of pipeline. Operators should vigorously develop the network resource, enhance core competitiveness and create core values. Thirdly, operators can create content and applications platform: To establish mobile SNS platform, which will become the most important type of business, because it has more accurate simulation of social relations. To develop App Store, which is of strategic significance to china operators, because the new software applications can reach consumers in the fastest pace? To develop new network communications and explore innovative services such as voice messaging, video calls and so on
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Mukherjee, Rahul. "Jio sparks Disruption 2.0: infrastructural imaginaries and platform ecosystems in ‘Digital India’." Media, Culture & Society 41, no. 2 (2018): 175–95. http://dx.doi.org/10.1177/0163443718818383.
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In recent years, Reliance Jio’s offer of 4G services, guaranteeing free voice calls and ‘unlimited’ data streaming, lead to disruption in the Indian telecom market with other cellular operators losing their revenue and customer base. To comprehensively analyze this churn in the Indian telecom industry and its impact on mobile phone customers, the article argues for observing the entanglement of infrastructural and platform-related discourses at three levels of operation: Jio’s strategies to capture the Indian telecom market and the responses by the leading incumbent service provider (Airtel), ordinary citizens’ phone use practices and infrastructural encounters, and the government’s vision for India’s digital future. Connecting pipes to platforms, Jio made infrastructural investments (in spectrum, cell towers, and fiber optics networks) to promote its suite of apps (JioTV, JioChat, and JioMoney). Ordinary citizens relate their access/proximity to telecom infrastructure (cell antennas) to their ability to effectively use apps on their phones. ‘Digital India’ vision purportedly facilitated infrastructural growth to create platforms that would support demonetization and facilitate transparent governance. Through such a three-pronged analysis, I conceptualize ‘infrastructural imaginaries’ that are coproduced by states and citizens, and lie at the intersection of structured state policy/corporate initiatives and lived experiences/affective encounters of ordinary citizens.
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Chhabra, Meenu, and Kumar Manoj. "A Study of telecom subscribers and strategy thereof: Role of Reliance JIO in Indian Telecom Industry." RESEARCH REVIEW International Journal of Multidisciplinary 4, no. 1 (2019): 586–90. https://doi.org/10.5281/zenodo.2552345.
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Indian telecom industry is the second largest in the world with a subscriber base of 1.18 billion. A tremendous growth in the past decade and half is recorded. In the present era of competition telecom industry players have made total transformation in their strategies from attracting new customers to retaining the existing customers and growth model to value added models. Mobile subscriptions continue to rise steadily, but the telecom sector finances will come under increasing strain in 2018. Present study aims at discussing the marketing and the customer retention strategies. The purpose of the study is to analyze the overall trends in the telecom and broadband customer base. Current research also highlights the trends of private market leaders that are Bharti Airtel, Idea and Vodafone. After the entry of Reliance JIO, telecommunication industry faced a complete change so efforts are made by the author to portray the role of reliance JIO in grooming telecom industry. It’s been found at the end that reliance JIO has totally changed the game and forced all the telecom service providers to lessen the calling and data services rates. That at last resulted into the increased total revenues of the telecom industry and the decreased average revenue per user (ARPU).
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Mokale, Mahesh. "Scalable Data Management Strategies for Telecommunications Enterprises." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 05, no. 12 (2021): 1–8. https://doi.org/10.55041/ijsrem11159.
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In the current technological landscape marked by the widespread adoption of 5G networks, the proliferation of Internet of Things (IoT) devices, and the ever-growing need for real-time data processing, telecommunications enterprises are encountering unprecedented challenges in managing and scaling their vast volumes of data. The digital age has brought about a transformative surge in the volume, variety, and velocity of data, compelling telecom companies to reevaluate and enhance their data management strategies to remain competitive. This surge is not limited to just an increase in the number of connected devices but also encompasses the complexity of data types—ranging from structured and unstructured customer data to high-frequency network performance metrics, sensor-generated data, and real-time analytics. The sheer scale and speed at which data is generated in the telecom industry make traditional data management frameworks insufficient. Without robust, scalable strategies in place, enterprises risk inefficiencies in operations, delays in decision-making, and missed opportunities for revenue growth and innovation. Therefore, adopting a forward-looking approach to data management is no longer optional but an absolute necessity. This paper delves into a range of innovative approaches to scalable data management, highlighting how cutting-edge technologies such as cloud computing, edge computing, process automation, and artificial intelligence (AI)-driven analytics can provide telecom companies with the tools they need to thrive in this data-driven era. Cloud adoption offers unmatched scalability and flexibility, while edge computing enables low-latency processing by bringing computational power closer to the data source. Additionally, automation simplifies complex workflows, and AI-powered analytics unlock actionable insights that can drive operational efficiency, enhance customer satisfaction, and create new revenue streams. By exploring these strategies, this paper aims to provide actionable insights and a roadmap for telecom companies to not only optimize their existing data infrastructure but also align their operations with emerging industry trends, ensuring long-term growth, resilience, and competitiveness in an increasingly interconnected world. Keywords: Scalable Data Management, Telecommunications Enterprises, 5G Networks, Internet of Things (IoT), Cloud Computing, Edge Computing, AI-Driven Analytics, DataOps Methodologies, Data Federation, Real-Time Data Processing, Blockchain for Data Security, Automation in Data Management, Hyper-Personalization, Regulatory Compliance
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Mishra, Aditya, and Ayushi Sharma. "From Feature Phone to Digital Inclusion: The Strategic Implications of Reliance JioPhone." OPJU Business Review 4, no. 1 (2025): 45–60. https://doi.org/10.63825/opjubr.2025.4.1.04.
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This research examines Reliance Jio's JioPhone initiative and its impact on the Indian telecom market. The study utilized personal interviews with common people and industry professionals from Reliance Jio, supplemented by a survey. This mixed-method approach provided a comprehensive understanding of the JioPhone's influence. Key findings indicate that the JioPhone has significantly accelerated smartphone adoption, democratized digital services, and helped bridge the digital divide. Positioned within Reliance Jio's ecosystem, the JioPhone has expanded the subscriber base and driven revenue growth. Competitors have recalibrated their strategies, intensifying market competition. The study reinforces factors like affordability and usability influencing consumer behavior. Recommendations for stakeholders and policymakers focus on addressing the identified challenges and leveraging the opportunities presented by the JioPhone initiative. This paper provides new insights into how a low-cost smartphone initiative can transform the telecom market, emphasizing the role of such initiatives in promoting digital inclusion and competition.
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J, JENIFA. "Customer Churn Prediction Using Machine Learning." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47804.
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Abstract - In today’s highly competitive telecom sector, customer churn — the loss of clients to competitors — poses a major threat to revenue and growth. This project tackles churn prediction using machine learning, focusing on the Random Forest algorithm to identify customers likely to leave. The Telco Customer Churn dataset, containing customer demographics, service usage, and account details, serves as the foundation.The workflow begins with exploratory data analysis (EDA) to uncover key trends and indicators of churn. A robust preprocessing pipeline is then applied, including handling missing data, encoding categories, scaling, and addressing class imbalance. Random Forest is chosen for its accuracy and interpretability, and its performance is compared against models like Logistic Regression, SVM, and XGBoost using metrics such as precision, recall, F1-score, and ROC-AUC.Results show that contract type, tenure, and billing-related features significantly influence churn. The model not only predicts churn with high accuracy but also provides actionable insights through feature importance and visualization tools. This supports data-driven retention strategies like targeted offers or improved services.Ultimately, the project showcases how machine learning enhances customer relationship management (CRM) and can be adapted for similar use cases in banking, insurance, and e-commerce. Key Words: Customer churn, churn prediction, Random Forest, machine learning, telecom industry, predictive modeling, supervised learning
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Hussain, Sajjad, Shahzad Mehmood Mehmood, Asim Masood, Azhar Naeem, and Mohammad Arfeen. "Customer Loyalty a Key to Success: A Case Study in Telecom Sector of Pakistan." Jinnah Business Review 9, no. 2 (2021): 103–11. http://dx.doi.org/10.53369/ekmt3171.
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This paper identified the role of the independent variable like service quality, taking perceived value, word of mouth and customer satisfaction (mediation/ intervening variables) in creating customer loyalty (dependent variable) among the telecom user (mobile phone users). The empirical portion have extensive literature regarding the mentioned variables and shown their impact towards the customer loyalty. The telecom industry has been facing cut throat competition due to the market saturation, decrease in ARPU (average revenue per user), and shift to internet based (cheaper sources) communication tools, unexpected mergers, higher cost and decreasing the margin. Thus, telecom companies have been thinking about devising the best possible suitable strategies for creating the customer to maintain their survival and growth. The simple random techniques are used for sample selection and self-administration questionnaire is the tool for collecting data. A sample of 300 universities students from Rawalpindi and Islamabad is base for analysis. Amos 20 is the software and SEM is the tool for extracting result. Dual relationship is tested likewise direct (service quality and customer loyalty) and indirect through mediating variables. Results showed that customer satisfaction is the strongest mediator in developing a high-quality customer loyalty service, and it has more effect than the direct link between quality of service and customer loyalty. It leads industrial professionals to develop a strategy based on customer satisfaction. It is concluded that customer satisfaction increases the level of the industrial professionalism. Hence the customer satisfaction increases the service quality and customer loyalty services. In nutshell, the cooperate image and switching barrier can be possible leads for the future research.
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Yusuf Onifade, Abiodun, Remilekun Enitan Dosumu, Abraham Ayodeji Abayomi, Oluwademilade Aderemi Agboola, and Uloma Stella Nwabekee. "Advances in Cross-Industry Application of Predictive Marketing Intelligence for Revenue Uplift." International Journal of Advanced Multidisciplinary Research and Studies 4, no. 6 (2024): 2301–12. https://doi.org/10.62225/2583049x.2024.4.6.4325.
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Predictive Marketing Intelligence (PMI) has emerged as a transformative approach that leverages advanced analytics, machine learning, and big data to anticipate consumer behaviors and optimize marketing strategies. Its cross-industry application has gained significant traction, providing businesses across sectors with actionable insights that enhance customer engagement, streamline operations, and drive substantial revenue uplift. This explores the evolution and implementation of PMI in various industries, including retail, finance, healthcare, telecommunications, and hospitality. Each sector has utilized predictive intelligence to address unique challenges ranging from personalized product recommendations in e-commerce to churn prediction in telecom and demand forecasting in travel and healthcare. A key contribution of PMI lies in its ability to unify disparate data sources such as CRM systems, web analytics, and social media activity to create dynamic customer profiles and deliver targeted, timely, and contextually relevant marketing interventions. These capabilities not only increase customer acquisition and retention but also optimize marketing spend and improve return on investment (ROI). Moreover, cross-industry analysis reveals transferable methodologies, such as behavioral segmentation and propensity modeling, which can be adapted to new contexts with significant effectiveness. This also highlights innovative case studies where PMI has yielded measurable revenue gains and operational efficiencies. While the benefits are clear, the implementation of PMI is not without challenges. Issues such as data privacy compliance, algorithmic bias, and the integration of legacy systems pose ongoing concerns. Nevertheless, emerging technologies including real-time analytics, generative AI, and edge computing are expanding the boundaries of predictive intelligence and paving the way for broader adoption. This review concludes that cross-industry application of PMI represents a critical lever for competitive advantage and sustained revenue growth. Organizations that invest in predictive capabilities and ethical data practices are well-positioned to thrive in an increasingly dynamic and customer-centric marketplace.